Constructing Situation Specific Belief Networks

TL;DR

This paper presents a method for building minimal, situation-specific belief networks from a knowledge base of network fragments, ensuring query completeness for probabilistic reasoning.

Contribution

It introduces definitions and conditions for constructing query-complete, situation-specific belief networks from network fragments, advancing knowledge-based probabilistic reasoning.

Findings

Defines query completeness and situation-specific networks

Provides conditions for knowledge base to guarantee query completeness

Discusses relationship to earlier KBMC work

Abstract

This paper describes a process for constructing situation-specific belief networks from a knowledge base of network fragments. A situation-specific network is a minimal query complete network constructed from a knowledge base in response to a query for the probability distribution on a set of target variables given evidence and context variables. We present definitions of query completeness and situation-specific networks. We describe conditions on the knowledge base that guarantee query completeness. The relationship of our work to earlier work on KBMC is also discussed.